The development of image sensor technology has made it possible to capture image data in hundreds of bands covering a broad spectrum. In contrast with trichromatic images, multispectral and hyperspectral imaging offer an information-rich representation of the scene due to their capability to capture imagery across many bands covering the visible and near infrared segments of the light spectrum. As a remote sensing tool, multispectral and hyperspectral imaging can used in aerial imaging, for example. Imaging spectroscopy has found many challenges and opportunities for terrestrial applications including colour reproduction, material recognition and shape recovery. Applications of spectral imaging in colorimetry include digital archiving of art and historical documents, textile production, printing and high dynamic range imaging.
Remote sensing imaging technologies coexist with ground-based systems based on liquid crystal tunable filters (LCTFs), acousto-optic tunable filters (AOTF), Fabry-Perot imagers and multiple-CCD cameras. These technologies comprise the staring arrays, pushbroom and multiple CCD spectral cameras.
One important aspect in acquiring images is the recovery of a hyperspectral or multispectral image from an on-chip filter array akin to the Bayer patterns, i.e. an array of of red-green and green-blue filters overlaid in alternating rows on the CCD or CMOS image sensor. For some sensors this filter array comprises multiple filters, often with spectral sensitivity functions comprising an exclusive wavelength range.
The process of de-Bayering, i.e. the recovery of a full colour image from the incomplete data delivered by a Bayer array, may employ green-red and green-blue filter cross talk or fixed ratios between the green and the other two colour channels. This is important since the cross-talk between filters overlaid on larger patterns may be quite low. This, in turn, implies that the correlation between the filters is difficult to be employed in a way similar to that often applied to de-Bayering approaches. Further, the spatial proximity between similar filters on the sensor can be much greater than in Bayer arrays.
FIG. 1a illustrates an RGB Bayer pattern 100, where ‘1’ represents a blue filter, ‘2’ represents a green filter and ‘3’ represents a red filter. These three colours may also be referred to as three bands.
FIG. 1b illustrates a 3×3 multispectral filter pattern 150 with nine different bands 1-9. Note that, for the green filters (labelled ‘2’) on the Bayer array 100, there is always another similar (green) filter which is adjacent. This, together with the correlation of the green channel with both, the red and blue ones, is the basis for the practice to interpolate the green channel first and, later on, do likewise with the red and blue channels.
In contrast, the 9-filter overlay 150 has no similar adjacent filter. Moreover, in addition to the distance between similar filters being much greater, the negligible cross-talk does not hint at any interpolation sequence or provides any ratios that can be used to constrain the demosaicing process (de-Bayering may also use the fact that the red-green to blue-green ratio should remain constant).
Further, for multispectral and hyperspectral images, the main focus is in spectra representation. This is, the modelling of the sampled spectra as a linear combination of a small basis set.
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